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  • Articles  (5)
  • Articles: DFG German National Licenses  (5)
  • artificial intelligence  (5)
  • Springer  (5)
  • 1995-1999  (1)
  • 1990-1994  (4)
  • 1960-1964
  • Nature of Science, Research, Systems of Higher Education, Museum Science  (5)
  • 1
    Electronic Resource
    Electronic Resource
    Dynamic Generation of Museum Web Pages: The Intelligent Labelling Explorer (1997)
    Springer
    Archives and Museum Informatics 11 (1997), S. 107-115 
    Details
    ISSN: 1573-7500
    Keywords: anaphora〉 ; artificial intelligence ; coherence ; hypertext ; labels ; simulated museum tour ; text generation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Information Science and Librarianship , Nature of Science, Research, Systems of Higher Education, Museum Science
    Notes: Abstract The first phase of the Intelligent Labelling Explorer project has built the ILEX-1.1 system, which uses artificial intelligence technology to generate descriptions of objects displayed in a museum gallery. Each description appears on a World Wide Web page, and the user can move from page to page, viewing the objects in any order, mimicking the experience of someone walking through the museum. Crucially, these descriptions aren't simply retrieved from a storage space, but are generated on demand by combining canned text with fully generated text in a coherent way. This use of dynamic hypertext allows ILEX-1.1 to generate descriptions appropriate to the expertise level of the user and to refer back to objects the user has already seen or to suggest objects the user might be interested in based on what objects they've chosen to look at so far. This paper discusses the advantages of dynamic hypertext and issues related to generating a text that hangs together well.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1009099015843
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  • 2
    Electronic Resource
    Electronic Resource
    Wissensbasierte Systeme — Utopie und Realität (1992)
    Springer
    Journal for general philosophy of science 23 (1992), S. 315-322 
    Details
    ISSN: 1572-8587
    Keywords: knowledge-based systems ; expert systems ; artificial intelligence ; philosophy of science ; philosophy of technology
    Source: Springer Online Journal Archives 1860-2000
    Topics: Philosophy , Nature of Science, Research, Systems of Higher Education, Museum Science
    Notes: Summary The following article is a response to K. Mainzer's ‘Knowledge-Based Systems; Remarks on the Philosophy of Technology and Artificial Intelligence’. We show, that Mainzer does not reach any of his aims to analyse the possibilities and limits of AI-technology. to reduce anxiousness and hostility against AI, which is motivated by phantastic speculations. to evaluate the factual impact of AI on our lives and on society. His article contributes on the contrary to phantastic speculations, which are not technologically justified in any way. There are two main reasons for his misleading view: (a) the state of the art of knowledge-based systems is incorrectly described; (b) the roots, paradigms and alternatives to AI are not in the least sufficiently analysed. We examine issues (a) and (b) in Chapter 1 and Chapter 2. In Chapter 3 we discuss, how the conclusions, which Mainzer draws, have to be modified. In analysing the lines of argumentation of Mainzer we try to clarify the methodological errors and the philosophical attitude of Mainzer, which is in many respects not adequate to the subject of the article.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01801455
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  • 3
    Electronic Resource
    Electronic Resource
    Die starke KI-These (1991)
    Springer
    Journal for general philosophy of science 22 (1991), S. 337-348 
    Details
    ISSN: 1572-8587
    Keywords: conceptual realism ; research program ; artificial intelligence ; predicate logic ; semantics ; strong AI-thesis ; Turing test
    Source: Springer Online Journal Archives 1860-2000
    Topics: Philosophy , Nature of Science, Research, Systems of Higher Education, Museum Science
    Notes: Summary The controversy about the strong AI-thesis was recently revived by two interrelated contributions stemming from J. R. Searle on the one hand and from P. M. and P. S. Churchland on the other hand. It is shown that the strong AI-thesis cannot be defended in the formulation used by the three authors. It violates some well accepted criterions of scientific argumentation, especially the rejection of essentialistic definitions. Moreover, Searle's ‘proof’ is not conclusive. Though it may be reconstructed in a conclusive manner, the modified proof is trivial. Beyond that, the most interesting aspect is formulated as an axiom that is not justified either. Therefore Searle's criticism of strong AI-thesis fails to be a convincing proof — it can be reduced to an unjustified presupposition.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01801214
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  • 4
    Electronic Resource
    Electronic Resource
    Knowledge-based systems (1990)
    Springer
    Journal for general philosophy of science 21 (1990), S. 47-74 
    Details
    ISSN: 1572-8587
    Keywords: artificial intelligence ; knowledge-based systems ; philosophy of science ; philosophy of technology
    Source: Springer Online Journal Archives 1860-2000
    Topics: Philosophy , Nature of Science, Research, Systems of Higher Education, Museum Science
    Notes: Summary No kind of technology has had such a profound effect upon our lives and society as the new knowledge-based systems which start to overcome the traditional computer technology. Few areas of science raise such high expectations and meet with so much sceptical resistance as Artificial Intelligence (AI). So it is the task of philosophy of science and technology to analyze the factual methodological possibilities of AI-technology. After a historical sketch of AI-development (Chapter 2), the technological foundations of expert systems are described (Chapter 3). It is a surprising result of analysis that expert systems are technical realizations of well-known philosophical methodologies. In this very sense, AI is not only technology, but philosophy too (Chapter 4). On the other hand the question arises if knowledge-based systems can support the work of philosophers of science who want to explain the process of scientific research, inventions, and discoveries. This application of AI for the philosophical professionals is discussed in the 5th chapter. In the 6th chapter some scenarios of AI-technology are described which are expected in the nineties. Then, besides philosophy of science and technology, we have to consider the ethical questions which arise in evaluating the factual impact of AI-technology on our lives and society.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01801416
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  • 5
    Electronic Resource
    Electronic Resource
    Künstliche Intelligenz und Philosophie (1990)
    Springer
    Journal for general philosophy of science 21 (1990), S. 347-358 
    Details
    ISSN: 1572-8587
    Keywords: artificial intelligence ; understanding ; representation ; meaning ; intentionality ; teleology ; subjectivity ; semiotics ; philosophical anthropology
    Source: Springer Online Journal Archives 1860-2000
    Topics: Philosophy , Nature of Science, Research, Systems of Higher Education, Museum Science
    Notes: Summary Artificial Intelligence can be considered as the so far last attempt to decode the anthropological comparison between human beings and machines. Thereby it also represents in a prominent way what can be called “systemic thought”. Searle's conclusive argument against strong AI (that is the idea of computers having intention in a literal way) refers to his precise distinction between syntax and semantics. This difference obviously opposing some of Searle's other essential ideas will only convince if it also explains the genetic-pragmatic aspect. A theory explaining the “life of mind” and the possibility of understanding needs to combine representation and intention with the subjective causation of signs. At the same time they have to be contextualized within a model of teleologically interpreted life recognized with the help of self-experience and self-reflection. This suggests that AI is a simulation which wrongly believes to be a real duplication. Actually it is a semiotic reduction (syntax and semantic surface of signs only) and a psychological compensation (Turing test) connected with a genetic or abductive fallacy. The biological decontextualization, in fact the elimination of teleology and intention, the deconstruction of subjectivity, the loss of the genetic-pragmatic dimension and the abductive fallacy induce the strong AI to confuse its surface-illusion of simulated understanding with the real process itself.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01801043
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